Positron Emission Tomography Detector Research Articles

The SNR of time-of-flight positron emission tomography data for joint reconstruction of the activity and attenuation images

Objective. Measurement of the time-of-flight (TOF) difference of each coincident pair of photons increases the effective sensitivity of positron emission tomography (PET). Many authors have analyzed the benefit of TOF for quantification and hot spot detection in the reconstructed activity images. However, TOF not only improves the effective sensitivity, it also enables the joint reconstruction of the tracer concentration and attenuation images. This can be used to correct for errors in CT- or MR-derived attenuation maps, or to apply attenuation correction without the help of a second modality. This paper presents an analysis of the effect of TOF on the variance of the jointly reconstructed attenuation and (attenuation corrected) tracer concentration images. Approach. The analysis is performed for PET systems that have a distribution of possibly non-Gaussian TOF-kernels, and includes the conventional Gaussian TOF-kernel as a special case. Non-Gaussian TOF-kernels are often observed in novel detector designs, which make use of two (or more) different mechanisms to convert the incoming 511 keV photon to optical photons. The analytical result is validated with a simple 2D simulation. Main results. We show that if two different TOF-kernels are equivalent for image reconstruction with known attenuation, then they are also equivalent for joint reconstruction of the activity and the attenuation images. The variance increase in the activity, caused by also jointly reconstructing the attenuation image, vanishes when the TOF-resolution approaches perfection. Significance. These results are of interest for PET detector development and for the development of stand-alone PET systems.

Search for a new material for a medical Cherenkov radiation detector

In this work, using Geant4, we simulate a time-of-flight positron emission tomography detector based on Cherenkov radiation. We consider various materials as a basis for the detector, including a pure PMMA and PMMA used as a matrix containing small resonant particles of copper and gold. For that, in CST studio, we determine the dielectric permittivity for a composite material, which we then use for simulations in Geant4. The resonant nature of the small metal particles allows producing Cherenkov photons by secondary electrons with lower energy, increasing the output of the radiated photons. We consider it as the way to increase temporal resolution as well as efficiency of the detector.

A study on the positioning of fine scintillation pixels in a positron emission tomography detector through deep learning of simulation data

In order to specify the location of the scintillation pixel that interacted with gamma rays in the positron emission tomography (PET) detector, conventionally, after acquiring a flood image, the location of interaction between the scintillation pixel and gamma ray could be specified through a pixel-segmentation process. In this study, the experimentally acquired signal was specified as the location of the scintillation pixel directly, without any conversion process, through the simulation data and the deep learning algorithm. To evaluate the accuracy of the specification of the scintillation pixel location through deep learning, a comparative analysis with experimental data through pixel segmentation was performed. In the same way as in the experiment, a detector was configured on the simulation, a model was built using the acquired data through deep learning, and the location was specified by applying the experimental data to the built model. Accuracy was calculated through comparative analysis between the specified location and the location obtained through the segmentation process. As a result, it showed excellent accuracy of about 85 %. When this method is applied to a PET detector, the position of the scintillation pixel of the detector can be specified simply and conveniently, without additional work.© 2017 Elsevier Inc. All rights reserved.

A continuous depth encoding PET detector using side readout of dual-layer GAGG crystals with SiPM array

A continuous depth encoding positron emission tomography (PET) detector using a side readout configuration with dual-layer GAGG scintillators of different decay times, coupled to a Silicon Photomultiplier (SiPM) array is proposed. The performance of the detector was evaluated through experimentation. The detector consists of an upper layer with a 1 × 4 fast decay GAGG (GAGG-F) crystal array and a lower layer with another 1 × 4 high-light-yield GAGG (GAGG-HL) crystal array. The 2 × 4 GAGG crystal array is then coupled to the 4 × 6 SiPM array. The SiPM array's sum signal is utilized for layer identification, while 24 individual signals are used to measure the 3D position of the gamma interaction. The experimental measurements demonstrate that the detector effectively resolves all crystal units and provides continuous depth information in the Z-direction. Utilizing the time over threshold method for dual-layer identification in coincidence mode yielded an accuracy of 96.4 %, whereas the pulse decay time method achieved an accuracy of 95.7 %. The average energy resolution was found to be 12.1 % and 11.2 % for the upper and lower GAGG crystal arrays, respectively. Using the maximum value-to-sum ratio method, the upper GAGG-F crystal layer displayed clear distinction and accurate assignment at two height positions, achieving a correct assignment rate of 90.5 %. In contrast, the lower GAGG-HL crystal layer exhibited poorer resolution at each height position, with correct assignment percentages dropping to 71.1 %. Employing the center of gravity position estimation method for the GAGG-F and GAGG-HL layers, the average Z spatial resolution was determined as 3.56 ± 0.33 mm (FWHM) and 3.35 ± 0.28 mm (FWHM).

A Preclinical Positron Emission Tomography (PET) and Electron-Paramagnetic-Resonance-Imaging (EPRI) Hybrid System: PET Detector Module.

We report the design and experimental validation of a compact positron emission tomography (PET) detector module (DM) intended for building a preclinical PET and electron-paramagnetic-resonance-imaging hybrid system that supports sub-millimeter image resolution and high-sensitivity, whole-body animal imaging. The DM is eight detector units (DU) in a row. Each DU contains 12×12 lutetium-yttrium oxyorthosilicate (LYSO) crystals having a 1.05 mm pitch read by 4×4 silicon photomultipliers (SiPM) having a 3.2 mm pitch. A small-footprint, highly-multiplexing readout employing only passive electronics is devised to produce six outputs for the DM, including two outputs derived from SiPM cathodes for determining event time and active DU and four outputs derived from SiPM anodes for determining energy and active crystal. Presently, we have developed two DMs that are 1.28×10.24 cm2 in extent and approximately 1.8 cm in thickness, with their outputs sampled at 0.7 GS/s and analyzed offline. For both DMs, our results show successfully discriminated DUs and crystals. With no correction for SiPM nonlinearity, the average energy resolution for crystals in a DU ranges from 14% to 16%. While not needed for preclinical imaging, the DM may support 300-400 ps time-of-flight resolution.

A-Si EPID Modeling in GATE for Monte Carlo Investigation on the Optical Properties of Gd<sub>2</sub>O<sub>2</sub>S:Tb and Lu<sub>2</sub>SiO<sub>5</sub>:Ce Scintillators

A detailed a-Si Electronic Portal Imaging Device (EPID) was implemented in GATE (Geant4 application for tomographic emission) toolkit for Monte Carlo simulations, employing the standard electromagnetic processes and optical photon processes. The composition of the scintillating material is varied using the conventional terbium-doped gadolinium oxysulfide phosphor (Gd2O2S:Tb) and cerium-doped lutetium oxyorthosilicate (Lu2SiO5:Ce) which is widely used in Positron Emission Tomography (PET) detectors due to its supremacy in aiding the detection of low-energy photons. It was found that the number of optical photons produced is higher when using the Lu2SiO5:Ce scintillator resulting in a slightly better signal-to-noise ratio (SNR). The scattering within the EPID components was also investigated where the majority of the detected secondary particles were created in the scintillator. The results also show that the copper plate layer of the EPID contributes to additional Compton electrons and bremsstrahlung and annihilation photons to the measurements in the scintillator and photodiode layer. The glass substrate, graphite plates, electronic components, and aluminum bottom cover are also found to contribute a huge fraction of backscattered particles to the measurements at the photodiode layer.

Colored reflectors to improve coincidence timing resolution of BGO-based time-of-flight PET detectors

Time-of-flight (TOF) positron emission tomography (PET) detectors improve the signal-to-noise ratio of PET images by limiting the position of the generation of two 511 keV gamma-rays in space using the arrival time difference between the two photons. Unfortunately, bismuth germanate (BGO), widely used in conventional PET detectors, was limited as a TOF PET scintillator due to the relatively slow decay time of the scintillation photons. However, prompt Cerenkov light in BGO has been identified in addition to scintillation photons. Using Cerenkov photons for timing has significantly improved the coincidence timing resolution (CTR) of BGO. Based on this, further research on improving the CTR for a BGO-based TOF PET system is being actively conducted. Wrapping materials for BGO pixels have primarily employed white reflectors to most efficiently collect scintillation light. White reflectors have customarily been used as reflectors for BGO pixels even after Cerenkov light began to be utilized for timing calculations in pixel-level experiments. However, when the arrival-time differences of the two 511 keV annihilations photons were measured with pure Cerenkov radiators, painting the lateral sides of the radiators black can improve CTR by suppressing the reflection of Cerenkov photons. The use of BGO for TOF PET detectors requires simultaneously minimizing scintillation loss for good energy information and suppressing reflected Cerenkov photons for better timing performance. Thus, reflectors for BGO pixels should be optimized for better timing and energy performance. In this study, colored polytetrafluoroethylene (PTFE) tapes with discontinuous reflectance values at specific wavelengths were applied as a BGO reflector. We hypothesized that CTR could be enhanced by selectively suppressing reflected Cerenkov photons with an optimum colored reflector on the BGO pixel while minimizing scintillation photon loss. CTRs were investigated utilizing white and three colors (yellow, red, and green) PTFE tapes as a reflector. In addition, black-painted PTFE tape and enhanced specular reflector film were investigated as reference reflector materials. When 3 × 3 × 20 mm3 BGO pixels were wrapped with the yellow PTFE reflector, the CTR was significantly improved to 365 ± 5 ps from 403 ± 14 ps measured with the conventional white PTFE reflector. Adequate energy information was still obtained with only 4.1% degradation in light collection compared to the white reflector. Colored reflectors show the possibility to further improve CTR for BGO pixels with optimum reflectance design.

Angular Irradiation Methods for DOI Calibration of Light-Sharing Detectors—A Perspective for PET In-System Calibration

Typical positron emission tomography (PET) detectors consist of one-layer segmented scintillators coupled to silicon photomultipliers (SiPMs). Light-sharing detectors, e.g., semi-monoliths, additionally provide depth-of-interaction (DOI) estimation, performing best when calibrated individually. To establish those designs in large PET systems, scalable (re-)calibration methods are needed, possibly transferable to assembled systems. Here, two DOI calibration methods, potentially allowing in-system calibration, are evaluated and compared with an established calibration scheme. Both methods are based on angular detector irradiation using a fan-beam slit collimator and gradient tree boosting (GTB) for 3-Dimensional (3D) position estimation. The positioning performance was assessed for irradiation angles between 0∘ (lateral) and 90∘ (detector normal). With lateral irradiation, a unique DOI position is given, whereas with angular irradiation a gamma-individual reference position must be retrieved. The first method employs one angular beam and calculates DOI from the beam path and planar position estimation. The second method uses two intersecting beams. The intersection defines DOI for gamma interactions that are spatially localized there. Those gamma photons are identified by light distribution comparison using a nearest-neighbor routine. The methods were evaluated on a semimonolithic LYSO slab detector (32×3.9×19 mm slabs). Both methods performed similarly to the benchmark lateral irradiation within 1 %, and 6 %, respectively, for shallow irradiation angles up to 45∘.

Development of a four-layer DOI PET detector using long crystals segmented by subsurface laser engraving

Since the spatial resolution and sensitivity of positron emission tomography (PET) scanners can be improved by using scintillation detectors with depth-of-interaction (DOI) capability, an original four-layer DOI detector using a pixelated crystal array has been developed in our group. For DOI identification, reflectors have been inserted between the crystals in each layer with a specific arrangement in order to cause light sharing between the layers of the crystal array. However, the precise fabrication of pixelated crystal arrays was challenging and expensive compared to monolithic arrays. In the current study, a four-layer DOI detector composed of long crystals segmented into four segments by applying subsurface laser engraving (SSLE) was proposed. LuYSiO5 (LYSO) crystals of 1 × 1× 20 mm3 were segmented into four segments in the largest dimension using SSLE. A 6 × 6 crystal array using the segmented crystals was prepared and mounted on a 4 × 4 channel multi-pixel photon counter (MPPC, 2 × 2 mm active area). The performance of the proposed detector was investigated and compared with that of original four-layer DOI detector composed of discrete crystals of 1 × 1× 5 mm3 in terms of the crystal identification, layer separation and energy resolution. The 2D position maps of the detectors were obtained by the Anger-logic calculation, and the crystal responses were clearly separated for both detectors. Average energy resolutions of 10.0% ± 1.0%, and 10.5% ± 0.9% at 511 keV were obtained for the proposed detector, and the original detector composed of the discrete crystals, respectively. The layer separation performance was evaluated using separation ratio, which was the ratio of true counts in a specific irradiated crystal in a layer to the total counts in all four crystals stacked on top of each other. The responses of all four layers were clearly separated with a separation ratio of over 0.89 for the proposed and original detectors, respectively. The performance of the proposed detector was well comparable to the original detector composed of the discrete crystals, while the fabrication of the segmented detector was precise and simple.

Unsupervised deep learning framework for data-driven gating in positron emission tomography.

Physiological motion, such as respiratory motion, has become a limiting factor in the spatial resolution of positron emission tomography (PET) imaging as the resolution of PET detectors continue to improve. Motion-induced misregistration between PET and CT images can also cause attenuation correction artifacts. Respiratory gating can be used to freeze the motion and to reduce motion induced artifacts. In this study, we propose a robust data-driven approach using an unsupervised deep clustering network that employs an autoencoder (AE) to extract latent features for respiratory gating. We first divide list-mode PET data into short-time frames. The short-time frame images are reconstructed without attenuation, scatter, or randoms correction to avoid attenuation mismatch artifacts and to reduce image reconstruction time. The deep AE is then trained using reconstructed short-time frame images to extract latent features for respiratory gating. No additional data are required for the AE training. K-means clustering is subsequently used to perform respiratory gating based on the latent features extracted by the deep AE. The effectiveness of our proposed Deep Clustering method was evaluated using physical phantom and real patient datasets. The performance was compared against phase gating based on an external signal (External) and image based principal component analysis (PCA) with K-means clustering (Image PCA). The proposed method produced gated images with higher contrast and sharper myocardium boundaries than those obtained using the External gating method and Image PCA. Quantitatively, the gated images generated by the proposed Deep Clustering method showed larger center of mass (COM) displacement and higher lesion contrast than those obtained using the other two methods. The effectiveness of our proposed method was validated using physical phantom and real patient data. The results showed our proposed framework could provide superior gating than the conventional External method and Image PCA.

A simulation study of 1D U-Net-based inter-crystal scatter event recovery of PET detectors

To achieve high spatial resolution of reconstructed images in positron emission tomography (PET), the size of the scintillation crystal element is set small in current PET systems, which greatly increases the inter-crystal scattering (ICS) frequency. The ICS is a type of Compton scattering of the gamma photons from one crystal element to its neighborhood element, which obscures the determination of the first interaction position. In this study, we propose a 1D U-Net convolutional neural network to predict the first interaction position, which provides a universal way to efficiently solve the ICS recovery problem. The network is trained using the dataset collected from the GATE Monte Carlo simulation. The 1D U-Net structure is applied due to its capability of synthesizing both low-level and high-level information, which shows superiority in solving the ICS recovery problem. After being well trained, the 1D U-Net can generate a prediction accuracy of 78.1%. Compared to the coincidence events only composed from two photoelectric gamma photons, the sensitivity is improved by 149%. The contrast-to-noise ratio of the reconstructed contrast phantom increases from 6.973 to 10.795 for the 16 mm hot sphere. Compared to the take-energy-centroid method, the spatial resolution of the reconstructed resolution phantom can obtain the best improvement of 33.46%. Compared with the previous deep learning method based on the fully connected network, the proposed 1D U-Net can work more stably with considerably fewer network parameters. The 1D U-Net network model shows good universality when predicting different phantoms, and the computation speed is fast.

Coincidence time resolution measurements for dual-ended readout PET detectors

Coincidence time resolution (CTR) is an important performance parameter of clinical positron emission tomography (PET) detectors, which is dependent on the parameters of the scintillation crystal, the timing measurement methods, and the electronics. In this work, CTRs of PET detectors using dual-ended readout of segmented LYSO arrays were measured with different timing measurement methods. The detector modules were composed of LYSO arrays of 8 × 8 with a crystal size of 3.10 × 3.10 × 20 mm3 or 13 × 13 with a crystals size of 1.88 × 1.88 × 20 mm3, coupled at each end to an 8 × 8 Hamamatsu SiPM array (S13361-3050NE-08) with pixel active area of 3.00 × 3.00 mm2 and pitch of 3.20 mm. The signals of the SiPM arrays were individually read out and processed by using the TOFPET2 ASICs. The CTRs of the detectors were measured after the timing alignment of the ASICs was performed. Timing measurement methods of the dual-ended readout detector such as the average time of the two SiPMs, the faster time of the two SiPMs, the time of the back SiPM, and the time of the front SiPM were compared. The average time of the two SiPMs provides the best CTR, which is explained by a simple model about the timing measurement methods of a dual-ended readout detector. The detector with one-to-one crystal-to-SiPM coupling provides better CTR than the detector with a crystal size smaller than the pixel size of the SiPM. The best CTR of 367 ± 6 ps was obtained by using the 8 × 8 LYSO array with unpolished lateral crystal surfaces and ESR reflectors. The CTR of the dual-ended readout detector can be improved if a DOI-dependent timing correction is used.

Decision Tree-Based Demultiplexing for Prism-PET.

Signal multiplexing is necessary to reduce a large number of readout channels in positron emission tomography (PET) scanners to minimize cost and achieve lower power consumption. However, the conventional weighted average energy method cannot localize the multiplexed events and more sophisticated approaches are necessary for accurate demultiplexing. The purpose of this paper is to propose a non-parametric decision tree model for demultiplexing signals in prismatoid PET (Prism-PET) detector module that consisted of 16 × 16 lutetium yttrium oxyorthosilicate (LYSO) scintillation crystal array coupled to 8 × 8 silicon photomultiplier (SiPM) pixels with 64:16 multiplexed readout. A total of 64 regression trees were trained individually to demultiplex the encoded readouts for each SiPM pixel. The Center of Gravity (CoG) and Truncated Center of Gravity (TCoG) methods were utilized for crystal identification based on the demultiplexed pixels. The flood histogram, energy resolution, and depth-of-interaction (DOI) resolution were measured for comparison using with and without multiplexed readouts. In conclusion, our proposed decision tree model achieved accurate results for signal demultiplexing, and thus maintained the Prism-PET detector module's high spatial and DOI resolution performance while using our unique light-sharing-based multiplexed readout.

Investigation of Faraday cage materials with low eddy current and high RF shielding effectiveness for PET/MRI applications

Objective. This study aims to evaluate radiofrequency (RF) shielding effectiveness (SE), gradient-induced eddy current, magnetic resonance (MR) susceptibility, and positron emission tomography (PET) photon attenuation of six shielding materials: copper plate, copper tape, carbon fiber fabric, stainless steel mesh, phosphor bronze mesh, and a spray-on conductive coating. Approach. We evaluated the six shielding materials by implementing them on identical clear plastic enclosures. We measured the RF SE and eddy current in benchtop experiments (outside of the MR environment) and in a 3T MR scanner. The magnetic susceptibility performance was evaluated in the same MR scanner. Additionally, we measured their effects on PET detectors, including global coincidence time resolution, global energy resolution, and coincidence count rate. Main results. The RF SEs for copper plate, copper tape, carbon fiber fabric, stainless steel mesh, phosphor bronze mesh, and conductive coating enclosures were 56.8 ± 5.8, 63.9 ± 4.3, 33.1 ± 11.7, 43.6 ± 4.5, 52.7 ± 4.6, and 47.8 ±7.1 dB, respectively, in the benchtop experiment. Copper plate and copper tape experienced the most eddy current at 10 kHz in the benchtop experiment and also generated the largest ghosting artifacts in the MR scanner. Stainless steel mesh had the highest mean absolute difference (7.6 ±0.2 Hz) compared to the reference in the MR susceptibility evaluation. The carbon fiber fabric and phosphor bronze mesh enclosures caused the largest photon attenuation, reducing the coincidence count rate by 3.3%, while the rest caused less than 2.6%. Significance. The conductive coating proposed in this study is shown to be a high-performance Faraday cage material for PET/MRI applications based on its overall performance in all the experiments conducted in this study, as well as its ease and flexibility of manufacturing. As a result, it will be selected as the Faraday cage material for our second-generation MR-compatible PET insert.

Evaluation of a modular all-in-one high-resolution PET detector and readout electronics setup

Objective. The all-in-one solution and modularity of the C13500 series TOF-PET detector modules (Hamamatsu Photonics K.K., Hamamatsu, Japan) make them a highly attractive candidate for the development of positron emission tomography (PET) systems. However, the commercially available portfolio targets clinical whole-body PET systems with a scintillation crystal cross area of 3.1 × 3.1 mm2. To extend the modules for high resolution (preclinical or organ specific) systems, the support for smaller scintillation crystals is required. Approach. In this work, a PET detector was developed based on the TOF-PET modules using a light sharing approach, 16 × 16 lutetium oxyorthosilicate (LSO) scintillation crystals with a size of 1.51 × 1.51 × 10.00 mm3 readout with 8 × 8 photosensor channels of size 3.0 × 3.0 mm2. In addition to hardware and software development, the optimized parameter settings for the adapted configuration were evaluated. Main Results. A factor of two in amplification of the analog signal compared to the minimum gain setting was necessary for an accurate crystal identification (peak-to-valley ratio 14.9 ± 5.9). A further increase to a factor of three was not determined as optimum as the time over threshold duration, thus pile-up probability, increased from 1032.1 ± 109.5 to 1789.5 ± 218.5 ns (photopeak position). With this amplification a full width at half maximum (FWHM) energy resolution of 14.1 ± 2.0% and a high linearity of the energy detection was obtained. A FWHM coincidence resolving time (CRT) of 313 ps was achieved by using a low timing threshold, increasing the bandwidth of the front-end circuit and using a narrow ± 1σ energy window. To approximately double the sensitivity and reduce the power consumption, the timing parameters were adjusted resulting in a FWHM CRT of 354 ps (±2σ). Significance. Based on the results obtained with the proof-of-concept detector setup, we confirm the modularity and flexibility of the all-in-one TOF-PET detector modules for the future development of application-specific high-resolution PET systems.

Inter-crystal scattering event identification using a novel silicon photomultiplier signal multiplexing method

Objective. Identifying the inter-crystal scatter (ICS) events and recovering the first interaction position enables the accurate determination of the line-of-response in positron emission tomography (PET). However, conventional silicon photomultiplier (SiPM) signal multiplexing methods based on two-dimensional (2D) charge-division circuits do not allow the detection of multiple gamma-ray interaction positions in a scintillation array coupled with a SiPM array. In this study, we propose a novel multiplexing method that can restore all the individual channel data from a smaller number of multiplexed channels using high-pass filters and neural networks. Approach. The number of output channels is reduced by summing the SiPM signals that have passed through high-pass filters with different time constants. Then, the signal amplitude of each SiPM channel is restored from the combined signal using an artificial neural network. This study explains the principle of this method in detail and demonstrates the results using 4:1 multiplexing as an example. The usefulness of this method was also demonstrated by its application in the identification of ICS events in 1-to-1 coupled LSO-SiPM PET detectors. Main results. The artificial neural network enabled accurate energy estimation for each SiPM channel. One of the high-pass filter sets with the lowest Cramér–Rao lower bound provided the best results, yielding R 2 value of 0.99 between the true and estimated signals. The energy and flood histograms generated using the best-estimated signals were in good agreement with the ground truth. Additionally, the proposed method accurately estimated 2D energy deposit distribution in the LSO crystal array, allowing ICS event identification. Significance. The proposed method is potentially useful for ICS event recovery with a reduced number of array signal readout channels from a SiPM array.

Monolithic scintillator PET detector by using light sharing between adjacent detector modules

A monolithic crystal-based positron emission tomography (PET) detector has a low cost and high sensitivity and allows determining 3D positions by scintillation light distribution. However, the edge effect inherent to scintillators deteriorates the position resolution of the detector toward the crystal borders due to the escape and reflection of the scintillation light. An increase in crystal thickness will improve the detection efficiency, but the edge effect becomes severe. To improve the position resolution and detection efficiency of scintillators, the light-sharing technique is developed. Two identical trapezoidal monolithic cerium-doped lutetium yttrium orthosilicate (LYSO) crystals with a bottom size of 25.80 × 25.80 mm2 and a thickness of 20 mm are optically coupled at one lateral face by an optical medium. The scintillation light near the optically coupled interface is jointly collected by two adjacent 8 × 8 SiPM arrays from the bottom faces. The SiPM signals are individually read out and processed by using the multichannel readout application-specific integrated circuits (ASICs) of TOFPET2 to provide a light distribution. The transverse positions and depth of interaction (DOI) are calculated from the measured light distribution. As expected, the optical glue with a refractive index of n = 1.68 shows better light sharing between two LYSO crystals than the coupling media of silicon grease (n = 1.40) and air. For the 20 mm thick monolithic LYSO-based PET detector, the transverse position resolution near the crystal edge is improved by nearly 30% by using the light-sharing method compared with the black-painted treatment. However, the DOI resolution near the edge of the crystal is not significantly improved, which may be attributed to the incomplete collection of scintillation light. The DOI resolution of the detector would be improved by using electronics with lower noise and SiPM arrays with smaller pixel.

Energy Calibration of MVT Digitizers in All-Digital Gamma Cameras

The multiple voltage threshold (MVT) digitizer implements data acquisition for the gamma camera by sampling pulses with all-digital electronics and recovering them with the prior pulse model. It has been employed in several nuclear science applications, such as positron emission tomography detectors, personal dosimeters, survey meters, and wastewater activity probes. In these applications, a wide dynamic range of energy is usually required to measure multiple energies accurately. However, the energy nonlinearity of the MVT digitizer constrains the dynamic range of energy. To calibrate the nonlinearity of digitizers in gamma cameras, we propose a novel method to acquire the mapping from digitizer energy to pulse energy by obtaining their scatter plot with a high-speed oscilloscope. To demonstrate our method, we use a gamma camera based on the silicon photomultiplier and an inorganic scintillator to detect gamma photons from a Na-22 radioactive source. We show that the mapping can be empirically modeled as the quadratic function for the MVT digitizer. We further perform the calibration on the MVT digitizer, showing that the average deviation between digitizer energy and pulse energy is reduced from 245 keV to 28 keV at 1274 keV. Moreover, we show the energy spectra obtained with different sequences of digitizer calibration and photoelectric converter calibration. The energy spectrum obtained with digitizer calibration and then photoelectric converter calibration shows the most minor distortion. This suggests that digitizer calibration should be performed before photoelectric converter calibration. It is reasonable to extend our method to other gamma cameras by simulating sampling patterns of corresponding digitizers. This provides a way to realize gamma spectrometry with higher accuracy and a wider dynamic range.

The SNR of Positron Emission Data With Gaussian and Non-Gaussian Time-of-Flight Kernels, With Application to Prompt Photon Coincidence.

It is well known that measurement of the time-of-flight (TOF) increases the information provided by coincident events in positron emission tomography (PET). This information increase propagates through the reconstruction and improves the signal-to-noise ratio in the reconstructed images. Takehiro Tomitani has analytically computed the gain in variance in the reconstructed image, provided by a particular TOF resolution, for the center of a uniform disk and for a Gaussian TOF kernel. In this paper we extend this result, by computing the signal-to-noise ratio (SNR) contributed by individual coincidence events for two different tasks. One task is the detection of a hot spot in the center of a uniform cylinder. The second one is the same as that considered by Tomitani, i.e. the reconstruction of the central voxel in the image of a uniform cylinder. In addition, we extend the computation to non-Gaussian TOF kernels. It is found that a modification of the TOF-kernel changes the SNR for both tasks in almost exactly the same way. The proposed method can be used to compare TOF-systems with different and possibly event-dependent TOF-kernels, as encountered when prompt photons, such as Cherenkov photons are present, or when the detector is composed of different scintillators. The method is validated with simple 2D simulations and illustrated by applying it to PET detectors producing optical photons with event-dependent timing characteristics.

Experimental evaluation of convolutional neural network-based inter-crystal scattering recovery for high-resolution PET detectors

Objective. One major limiting factor for achieving high resolution of positron emission tomography (PET) is a Compton scattering of the photon within the crystal, also known as inter-crystal scattering (ICS). We proposed and evaluated a convolutional neural network (CNN) named ICS-Net to recover ICS in light-sharing detectors for real implementations preceded by simulations. ICS-Net was designed to estimate the first-interacted row or column individually from the 8 × 8 photosensor amplitudes. Approach. We tested 8 × 8, 12 × 12, and 21 × 21 Lu2SiO5 arrays with pitches of 3.2, 2.1, and 1.2 mm, respectively. We first performed simulations to measure the accuracies and error distances, comparing the results to previously studied pencil-beam-based CNN to investigate the rationality of implementing fan-beam-based ICS-Net. For experimental implementation, the training dataset was prepared by obtaining coincidences between the targeted row or column of the detector and a slab crystal on a reference detector. ICS-Net was applied to the detector pair measurements with moving a point source from the edge to center using automated stage to evaluate their intrinsic resolutions. We finally assessed the spatial resolution of the PET ring. Main results. The simulation results showed that ICS-Net improved the accuracy compared with the case without recovery, reducing the error distance. ICS-Net outperformed a pencil-beam CNN, which provided a rationale to implement a simplified fan-beam irradiation. With the experimentally trained ICS-Net, the degree of improvements in intrinsic resolutions were 20%, 31%, and 62% for the 8 × 8, 12 × 12, and 21 × 21 arrays, respectively. The impact was also shown in the ring acquisitions, achieving improvements of 11%–46%, 33%–50%, and 47%–64% (values differed from the radial offset) in volume resolutions of 8 × 8, 12 × 12, and 21 × 21 arrays, respectively. Significance. The experimental results demonstrate that ICS-Net can effectively improve the image quality of high-resolution PET using a small crystal pitch, requiring a simplified setup for training dataset acquisition.